Global summary

Identifying changes in the reproduction number, rate of spread, and doubling time during the course of the COVID-19 outbreak whilst accounting for potential biases due to delays in case reporting both nationally and subnationally. These results are impacted by changes in testing effort, increases and decreases in testing effort will increase and decrease reproduction number estimates respectively (see Methods for further explanation).

Using data available up to the: 2020-04-27

Note that it takes time for infection to cause symptoms, to get tested for SARS-CoV-2 infection, for a positive test to return and ultimately to enter the case data presented here. In other words, today’s case data are only informative of new infections about two weeks ago. This is reflected in the plots below, which are by date of infection.

Expected daily confirmed cases by country


Figure 1: The results of the latest reproduction number estimates (based on estimated confirmed cases with a date of infection on the 2020-04-17) can be summarised by whether confirmed cases are likely increasing or decreasing. This represents the strength of the evidence that the reproduction number in each region is greater than or less than 1, respectively (see the methods for details). Countries with fewer than 60 confirmed cases reported on a single day are not included in the analysis (light grey) as there is not enough data to reliably estimate the reproduction number.

Summary of latest reproduction number and confirmed case count estimates by date of infection


Figure 1: Confirmed cases with date of infection on the 2020-04-17 and the time-varying estimate of the effective reproduction number (light bar = 90% credible interval; dark bar = the 50% credible interval.). Regions are ordered by the number of expected daily confirmed cases and shaded based on the expected change in daily confirmed cases. The horizontal dotted line indicates the target value of 1 for the effective reproduction no. required for control and a single case required for elimination.

Reproduction numbers over time in the six regions expected to have the most new confirmed cases


Figure 2: Time-varying estimate of the effective reproduction number (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in the regions expected to have the highest number of new confirmed cases. Estimates from existing data are shown up to the 2020-04-17 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The horizontal dotted line indicates the target value of 1 for the effective reproduction no. required for control. The vertical dashed line indicates the date of report generation.

Reported confirmed cases and their estimated date of infection in the six regions expected to have the most new confirmed cases


Figure 3: Confirmed cases by date of report (bars) and their estimated date of infection (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in the regions expected to have the highest number of new confirmed cases. Estimates from existing data are shown up to the 2020-04-17 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The vertical dashed line indicates the date of report generation.

Reproduction numbers over time in all regions


Figure 4: Time-varying estimate of the effective reproduction number (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in all regions. Estimates from existing data are shown up to the 2020-04-17 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The horizontal dotted line indicates the target value of 1 for the effective reproduction no. required for control. The vertical dashed line indicates the date of report generation.

Reported confirmed cases and their estimated date of infection in all regions

Figure 5: Confirmed cases by date of report (bars) and their estimated date of infection (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in all regions. Estimates from existing data are shown up to the 2020-04-17 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The vertical dashed line indicates the date of report generation.

Latest estimates (as of the 2020-04-17)

Table 1: Latest estimates (as of the 2020-04-17) of the number of confirmed cases by date of infection, the effective reproduction number, and the doubling time (when negative this corresponds to the halving time) in each region. The mean and 90% credible interval is shown.
Country/Region New confirmed cases by infection date Expected change in daily cases Effective reproduction no. Doubling/halving time (days)
Afghanistan 101 (57 – 143) Likely increasing 1.3 (1 – 1.6) 13 (5.4 – -35)
Algeria 122 (70 – 167) Unsure 1.1 (0.8 – 1.4) 67 (9.5 – -13)
Argentina 165 (112 – 210) Likely increasing 1.2 (1 – 1.5) 18 (7.7 – -53)
Armenia 83 (38 – 127) Likely increasing 1.3 (0.8 – 1.7) 15 (5.3 – -18)
Australia 29 (2 – 53) Unsure 1 (0.3 – 1.6) -14 (5.5 – -3.1)
Austria 86 (43 – 134) Unsure 1 (0.6 – 1.3) -270 (8.8 – -8.1)
Azerbaijan 51 (15 – 88) Unsure 1.1 (0.6 – 1.7) 38 (5.1 – -7.1)
Bahrain 185 (120 – 262) Increasing 1.5 (1.1 – 1.9) 6.6 (4.1 – 16)
Bangladesh 411 (324 – 476) Likely increasing 1.1 (1 – 1.3) 37 (14 – -53)
Belarus 728 (617 – 821) Increasing 1.2 (1.1 – 1.4) 15 (9.8 – 35)
Belgium 1112 (984 – 1228) Likely decreasing 0.9 (0.9 – 1) -42 (340 – -20)
Bolivia 78 (32 – 117) Increasing 1.5 (1 – 2) 8.3 (3.9 – -62)
Bosnia and Herzegovina 46 (16 – 75) Unsure 1.1 (0.7 – 1.6) 45 (5.5 – -7.3)
Brazil 3954 (3698 – 4165) Increasing 1.3 (1.2 – 1.3) 15 (12 – 21)
Bulgaria 84 (40 – 126) Increasing 1.5 (1 – 2) 9 (4.1 – -45)
Cameroon 105 (60 – 146) Increasing 1.5 (1 – 1.9) 8.2 (4.4 – 59)
Canada 1712 (1567 – 1860) Unsure 1 (1 – 1.1) 170 (37 – -64)
Chile 509 (426 – 591) Likely increasing 1.1 (1 – 1.2) 40 (15 – -57)
China 31 (0 – 58) Likely decreasing 0.7 (0.2 – 1.3) -4.3 (13 – -2)
Colombia 254 (195 – 313) Increasing 1.2 (1 – 1.4) 19 (8.8 – -160)
Cote dIvoire 64 (25 – 100) Likely increasing 1.2 (0.8 – 1.7) 20 (5.1 – -10)
Croatia 51 (9 – 91) Unsure 1.3 (0.6 – 1.9) 16 (3.7 – -7.2)
Cuba 64 (24 – 98) Unsure 1.1 (0.7 – 1.5) 69 (6.5 – -8.1)
Czechia 91 (46 – 132) Likely decreasing 0.9 (0.6 – 1.1) -19 (20 – -6.5)
Denmark 191 (130 – 240) Unsure 1.1 (0.9 – 1.3) 61 (12 – -19)
Djibouti 46 (4 – 84) Likely decreasing 0.8 (0.3 – 1.2) -6.9 (13 – -2.8)
Dominican Republic 219 (142 – 273) Unsure 0.9 (0.7 – 1.1) -30 (31 – -10)
Ecuador 413 (320 – 485) Unsure 1.1 (0.9 – 1.2) 26 (11 – -81)
Egypt 237 (176 – 297) Increasing 1.2 (1 – 1.5) 17 (7.8 – -150)
Equatorial Guinea 60 (19 – 96) Increasing 2.5 (1.3 – 3.7) 3.5 (2 – 12)
Estonia 33 (6 – 59) Unsure 1.2 (0.5 – 1.8) 110 (4.2 – -5)
Finland 130 (74 – 187) Unsure 1 (0.8 – 1.3) -1200 (11 – -11)
France 1726 (1576 – 1902) Decreasing 0.9 (0.9 – 1) -110 (73 – -31)
Germany 2084 (1908 – 2246) Decreasing 0.9 (0.9 – 1) -32 (-110 – -19)
Ghana 68 (31 – 101) Unsure 1 (0.7 – 1.3) -88 (8.9 – -7.6)
Greece 57 (15 – 100) Likely increasing 1.4 (0.7 – 2) 9 (3.4 – -16)
Guinea 96 (40 – 137) Likely increasing 1.4 (1 – 1.8) 11 (4.6 – -35)
Honduras 45 (13 – 73) Increasing 1.8 (1 – 2.6) 6 (2.7 – -30)
Hungary 95 (45 – 141) Unsure 1.1 (0.7 – 1.4) 100 (8.1 – -9.7)
Iceland 76 (0 – 219) Unsure 3.7 (0 – 8.9) -12 (1.5 – -1.9)
India 1645 (1506 – 1797) Increasing 1.1 (1.1 – 1.2) 25 (16 – 63)
Indonesia 379 (298 – 447) Likely increasing 1.1 (0.9 – 1.2) 46 (14 – -38)
Iran 1138 (1005 – 1264) Decreasing 0.9 (0.8 – 1) -30 (-150 – -17)
Iraq 55 (19 – 88) Likely increasing 1.3 (0.8 – 1.9) 12 (4 – -14)
Ireland 605 (513 – 700) Unsure 1 (0.9 – 1.1) -98 (33 – -20)
Israel 303 (231 – 368) Unsure 1 (0.9 – 1.2) 77 (15 – -24)
Italy 2784 (2580 – 2980) Likely decreasing 0.9 (0.9 – 1) -52 (-590 – -27)
Japan 435 (353 – 513) Unsure 1 (0.8 – 1.1) -55 (37 – -15)
Kazakhstan 160 (110 – 215) Likely increasing 1.2 (0.9 – 1.4) 20 (7.8 – -36)
Kosovo 47 (12 – 80) Unsure 1.2 (0.7 – 1.8) 20 (4.3 – -7.7)
Kuwait 208 (145 – 263) Increasing 1.3 (1.1 – 1.6) 12 (6.4 – 67)
Kyrgyzstan 34 (1 – 63) Unsure 1.2 (0.5 – 1.9) 58 (3.8 – -4.5)
Latvia 27 (1 – 51) Unsure 1.4 (0.5 – 2.2) 23 (2.8 – -4.3)
Lebanon 28 (0 – 56) Likely increasing 2.4 (0.4 – 4.6) 4.2 (0.47 – -0.81)
Lithuania 28 (2 – 52) Unsure 0.8 (0.3 – 1.3) -7.3 (9.3 – -2.7)
Luxembourg 39 (10 – 71) Unsure 1.1 (0.5 – 1.6) -47 (5.8 – -4.6)
Malaysia 81 (39 – 125) Unsure 1.1 (0.7 – 1.4) 57 (7.1 – -9.4)
Mexico 1071 (950 – 1191) Increasing 1.3 (1.2 – 1.4) 13 (9.4 – 21)
Moldova 176 (119 – 227) Increasing 1.3 (1 – 1.5) 13 (6.6 – -730)
Morocco 182 (118 – 236) Unsure 1 (0.8 – 1.2) -120 (15 – -12)
Netherlands 768 (665 – 872) Decreasing 0.9 (0.8 – 1) -23 (-94 – -13)
New Zealand 40 (0 – 106) Unsure 3.1 (0 – 6.5) 16 (0.42 – -0.29)
Niger 36 (0 – 69) Unsure 1.8 (0.3 – 3.2) -63 (1.8 – -2.6)
Nigeria 116 (66 – 173) Increasing 1.4 (1 – 1.8) 11 (5.2 – -75)
North Macedonia 47 (15 – 77) Unsure 1.1 (0.6 – 1.6) -88 (5.8 – -5.2)
Norway 86 (44 – 130) Unsure 1 (0.7 – 1.3) -66 (9.8 – -7.6)
Oman 104 (56 – 147) Unsure 1 (0.7 – 1.3) 580 (9.7 – -10)
Pakistan 793 (681 – 892) Increasing 1.2 (1.1 – 1.4) 16 (11 – 35)
Palestine 51 (0 – 169) Unsure 3 (0 – 6.8) 130 (0.71 – -0.42)
Panama 185 (125 – 240) Unsure 1.1 (0.8 – 1.3) 94 (12 – -16)
Peru 1952 (1766 – 2114) Increasing 1.3 (1.2 – 1.4) 12 (9.1 – 16)
Philippines 190 (115 – 258) Unsure 1 (0.8 – 1.2) -90 (15 – -11)
Poland 360 (282 – 425) Unsure 1 (0.8 – 1.1) -66 (31 – -16)
Portugal 501 (408 – 576) Unsure 0.9 (0.8 – 1.1) -74 (38 – -19)
Puerto Rico 65 (26 – 95) Unsure 1.2 (0.8 – 1.6) 23 (5.8 – -12)
Qatar 716 (608 – 811) Increasing 1.3 (1.1 – 1.4) 15 (9.9 – 34)
Romania 336 (251 – 397) Unsure 1 (0.9 – 1.2) -280 (21 – -18)
Russia 5535 (5240 – 5812) Increasing 1.1 (1 – 1.2) 38 (25 – 79)
Saudi Arabia 1172 (1044 – 1291) Increasing 1.1 (1 – 1.2) 31 (17 – 260)
Senegal 64 (30 – 100) Increasing 1.8 (1.2 – 2.5) 5.5 (3 – 33)
Serbia 231 (173 – 286) Decreasing 0.8 (0.7 – 1) -16 (-180 – -8.4)
Singapore 896 (776 – 1004) Likely increasing 1.1 (0.9 – 1.2) 100 (23 – -43)
Slovakia 67 (16 – 114) Unsure 1.1 (0.7 – 1.7) 92 (5.6 – -6.3)
Somalia 39 (9 – 64) Unsure 1.2 (0.6 – 1.6) 47 (5.1 – -6.5)
South Africa 234 (164 – 303) Likely increasing 1.2 (1 – 1.5) 20 (8.4 – -59)
South Korea 26 (0 – 52) Unsure 1.4 (0.2 – 2.5) -69 (2.3 – -2.9)
Spain 5025 (4769 – 5300) Increasing 1.1 (1 – 1.1) 55 (30 – 290)
Sweden 710 (599 – 808) Increasing 1.1 (1 – 1.2) 31 (15 – -270)
Switzerland 209 (151 – 268) Likely decreasing 0.8 (0.6 – 1) -15 (-6600 – -7.7)
Thailand 36 (8 – 60) Unsure 1.2 (0.7 – 1.7) 20 (4.2 – -7.5)
Tunisia 27 (0 – 50) Unsure 1.2 (0.4 – 2.1) -17 (3.1 – -2.8)
Turkey 3111 (2896 – 3305) Decreasing 0.8 (0.8 – 0.9) -21 (-31 – -15)
Ukraine 501 (424 – 584) Likely increasing 1.1 (1 – 1.2) 44 (16 – -54)
United Arab Emirates 516 (421 – 600) Likely increasing 1.1 (1 – 1.2) 27 (13 – -290)
United Kingdom 4857 (4573 – 5099) Likely decreasing 1 (0.9 – 1) -100 (290 – -43)
United Republic of Tanzania 51 (6 – 92) Likely increasing 1.5 (0.7 – 2.3) 11 (3.1 – -7.8)
United States of America 30645 (29912 – 31292) Increasing 1 (1 – 1.1) 160 (74 – -1000)
Uzbekistan 61 (21 – 97) Unsure 0.9 (0.5 – 1.3) -24 (9.3 – -5.4)